Underwater Image Restoration by Red-Dark Channel Prior and Point Spread Function Deconvolution
Date Issued
2015
Date
2015
Author(s)
Cheng, Chia-Yang
Abstract
In the field of undersea research, underwater vehicles usually carry camera systems for recording. The captured images and videos often have two undesired characteristics: color distortion and low visibility. This is because that the light is exponentially attenuated while penetrating through water. Furthermore, the quantity of attenuation is associated with the wavelength of light spectrum. This thesis simplifies the Jaffe-McGlamery optical model and proposes an effective algorithm to recover underwater images. In our approach, a red-dark channel prior was defined and derived to estimate the background light and the transmission. The visibility of scene was compensated by the object-camera distance to recover the color of the background and objects. Subsequently, by analyzing the physical property of the point spread function, we developed a simple but efficient low-pass filter to deblur the image by deconvolution. Finally, we used the relationship between the radiance above the sea surface and the absorption coefficient to correct the color distortion. A wide variety of underwater images with different scenarios were used for the experiments. The experimental results show that the proposed algorithm effectively recovered underwater images while eliminating the influence of absorption and scattering. Comparing with many existing methods, the proposed framework provided more natural restoration results. We believe that this new restoration algorithm is promising in many underwater image processing applications.
Subjects
underwater image
image restoration
red-dark channel prior
point spread function deconvolution
wavelength and depth compensation
Type
thesis
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